Optimization of Application Deployment Delay with Efficient Task Scheduling in Cloud-Based Smart Home Platform

J. Rajkumar, Chuan Pham, K. Nguyen, M. Cheriet
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引用次数: 1

Abstract

Smart home platform is an incarnation of Internet of Things (IoT) system. In such a platform, home applications are deployed using Software as a Service (SaaS) deployment model, a new way of software service provisioning for quick application deployment. However, this deployment model still has deployment performance issues due to the high degree of coordination and mutual dependencies of distributed services built on heterogeneous technologies. In a large scale deployment setup with more number of services, inter and intra-communication links between the coordinated services increase thereby introducing execution delays at service computation, and inter-service communications. Therefore, in this paper, we propose a smart home platform architecture based on Platform as a Service (PaaS) model supporting the SaaS deployment model. Based on the designed architecture, we model an optimization problem named as optimized IoT Application Deployment (OIAD) to minimize application deployment time (total execution time). To solve the OIAD problem, this paper proposes a heuristic algorithm to find a near-optimal deployment time. The results of our simulation show an improvement in comparison with FCFS (First Come First Serve) and Random execution algorithm under various deployment scenarios and strategies.
基于云的智能家居平台中高效任务调度的应用部署延迟优化
智能家居平台是物联网(IoT)系统的化身。在这种平台中,家庭应用程序使用软件即服务(SaaS)部署模型进行部署,这是一种快速部署应用程序的软件服务提供新方式。然而,由于构建在异构技术上的分布式服务的高度协调和相互依赖,这种部署模型仍然存在部署性能问题。在具有更多服务数量的大规模部署设置中,协调服务之间的内部和内部通信链路增加,从而在服务计算和服务间通信中引入执行延迟。因此,本文提出了一种基于平台即服务(PaaS)模型的智能家居平台架构,支持SaaS部署模式。基于所设计的架构,我们建模了一个优化问题,称为优化物联网应用部署(OIAD),以最小化应用部署时间(总执行时间)。为了解决OIAD问题,本文提出了一种启发式算法来寻找接近最优的部署时间。仿真结果表明,在各种部署场景和策略下,与FCFS(先到先服务)和随机执行算法相比,该算法有了很大的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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